class_docstr: Implementation of Dataset class
  
  This is a simple implementation of loading and processing dataset for GATNE model.
  
  Args:
      config: dict, some configure parameters.
class_docstr_tok: ["Implementation","of","Dataset","class","This","is","a","simple","implementation","of","loading","and","processing","dataset","for","GATNE","model",".","Args",":","config",":","dict",",","some","configure","parameters","."]
docstr: Generate random walks for every edge type.
          
docstr_tok: ["Generate","random","walks","for","every","edge","type","."]
code: def generate_walks(self):
      """Generate random walks for every edge type."""
      all_walks = {}
      for e_type in self.edge_types:
          layer_walks = self.simulate_walks(
              edge_type=e_type,
              num_walks=self.config["num_walks"],
              walk_length=self.config["walk_length"],
          )
  
          all_walks[e_type] = layer_walks
  
      return all_walks
  
file_path: PGL/legacy/examples/GATNE/Dataset.py
imports: import sys
  import os
  import tqdm
  import numpy
  import logging
  import random
  from pgl import heter_graph
  import pickle
label_desc: Use image node_id 6 for calling the Dataset obj's underlying member method code with example usage: obj.generate_walks() and returns: all_walks